Differential linear brain growth patterns in preterm neonates based on birth gestational age and steroid exposure: A retrospective chart review
Bibliographic record
Abstract
OBJECTIVE: To assess the differences in brain growth between extreme preterm [EP](22-28wks gestation age [GA]) and very preterm infants [VP](28+1-32wks GA) using two-dimensional cranial ultrasound(cUS) at term equivalence. STUDY DESIGN: Retrospective study of neonates born at GA of ≤ 32 weeks between 1st January 2019 and 31st December 2022, without major parenchymal brain injury. RESULTS: 326 neonates, with 207 EP and 119 VP, were enrolled. EP infants compared to VP had significantly lower biparietal diameter [7.7vs7.9 cm, p = 0.003], corpus-callosum length [3.8vs4.1 cm, p < 0.001], corpus-callosum-fastigial distance [4.5vs4.8 cm, p = 0.004] and cerebellar-vermis height [2.1vs2.2 cm, p = 0.002]. Cumulative postnatal steroid exposure had no significant association with brain metrics; however, exposure to antenatal steroids was negatively associated with corpus-callosum length [β = -0.38 (-0.58 to -0.7),p = 0.0003] and pons anteroposterior depth [β = -0.36 (-0.47 to -0.25),p < 0.0001] despite adjustments for clinically important risk factors. CONCLUSION: Preterm infants born ≤ 28 weeks GA have significantly smaller dimensions of major white matter tracts than preterm infants born 28-32 weeks GA at term equivalence. Exposure to antenatal steroids negatively impacts corpus-callosum length and pons anteroposterior depth.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".